{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas import Series, DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sep    57\n",
       "Oct    52\n",
       "Nov    50\n",
       "Dec    45\n",
       "Jan    46\n",
       "Feb    40\n",
       "Mar    41\n",
       "Apr    40\n",
       "May    43\n",
       "Jun    56\n",
       "dtype: int64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = np.random.default_rng(0)\n",
    "months = 'Sep Oct Nov Dec Jan Feb Mar Apr May Jun'.split()\n",
    "\n",
    "s = Series(g.integers(40, 60, 10),\n",
    "          index=months)\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sep    90.0\n",
       "Oct    85.0\n",
       "Nov    83.0\n",
       "Dec    78.0\n",
       "Jan    79.0\n",
       "Feb    73.0\n",
       "Mar    74.0\n",
       "Apr    73.0\n",
       "May    76.0\n",
       "Jun    89.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s + (80 - s.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
